RETRACTED: Color perception and recognition method for Guangdong embroidery image based on discrete mathematical model

Zhang, Ya; Xiong, Qingrong

doi:10.1177/1063293x21994361

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…If the images with the same aesthetic statistical characteristics describe different contents, the emotions expressed by the images are often different. These problems cannot be solved only based on the aesthetic characteristics [17,18]. Generally speaking, the emotion classification method based on aesthetics needs to solve the problem of multifeature selection and deeper image semantic gap.…”

Section: Experiments and Analysismentioning

confidence: 99%

Image Color Recognition and Optimization Based on Deep Learning

2022

Wireless Communications and Mobile Computing

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In order to solve the problem of image color recognition, this paper proposes a method of image color recognition and optimization based on deep learning and designs a postprocessing framework based on word bag model (bow). The framework uses CNN features and calculates feature similarity. The image sets with high similarity are input into the image classifier trained by bow clustering model as the preliminary retrieval results. The retrieval results are the categories with the largest number of images. The experimental results show that the image retrieval accuracy of the framework is 90.4% based on the same data set and classification category, which is 10% higher than the image retrieval algorithm based on CNN features. Conclusion. The color matching degree between the image color and the image to be retrieved has been greatly improved.

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Section: Experiments and Analysismentioning

confidence: 99%

Image Color Recognition and Optimization Based on Deep Learning

2022

Wireless Communications and Mobile Computing

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“…27 developed a new method to detect the color of cashmere using image analysis and studied the application of color in length measurement. In the literature, Zhang and Xiong 28 proposed a method for color perception and recognition of Cantonese embroidery images based on a discrete mathematical model. In the literature, Yang and He 29 established a color matching model based on the Kubelka–Munk theory based on experimental results.…”

Section: Application Of Cprm In Fabric Color Representationmentioning

confidence: 99%

CPRM: Color perception and representation model for fabric image based on color sensitivity of human visual system

Zhao

Han

Shi

et al. 2023

Textile Research Journal

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As an important attribute of fabric appearance and the first element that affects vision, color plays an important part in fabric and garment design, development, production and sales. Fabrics are becoming increasingly colorful which raises the difficulty of automatic recognition. With the development of computer vision technology, it has become a mainstream research hotspot to process and recognize fabric colors through novel computer vision techniques. In this paper, a color perception and representation model (CPRM) for fabric image based on color sensitivity of the human visual system is proposed to deal with the color changes caused by the human eye’s perception of fabric appearance. Inspired by the human visual biological mechanisms, we designed a CPRM by using the color sensitive function. In order to verify the effectiveness of the proposed CPRM, two types of computer simulation experiments are simulated, which are color shifts and color matching. The former verifies that our proposed model can effectively simulate the human visual system in color perception actions, which is consistent with the results verified by biological experimental data; the latter shows that the proposed model’s synergy of assimilation and contrast is closer to the biological model during the color perception stage. Finally, the CPRM is applied on three different fabric image data sets, and extensive experiments are simulated by the proposed CPRM. The CPRM could not only effectively characterize the color contrasts, but also accurately express the color changes caused by the fine adjustment of dyed fibers. The experimental results show the validity of the proposed CPRM, which can effectively perceive and represent fabric color. The proposed CPRM has important application prospects in improving color matching efficiency and intelligent production level in the textile industry.

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“…Zhang et al [12] in Perception and identification of colours in Canton embroidery weaving through discrete mathematical models to help build a colour database for Canton embroidery. Vryzidis et al [13] discussed different types of textiles used for sanctuary door curtains in Orthodox churches during the Ottoman period, illustrating the connection between Byzantine traditions and the Ottoman cultural environment in terms of images and their symbolic meaning; Chung-Feng Jeffrey Kuo et al [14] Pattern-making simulation on embroidery using probabilistic neural network and texture fitting method", based on a probabilistic neural network, texture fitting method to visually simulate the real effect of embroidery.…”

Section: ) Identification and Image Analysis Of Embroidered Fabricsmentioning

confidence: 99%

Hot Spots and Frontiers in Embroidery Research: A Visualization Analysis via CiteSpace Based on WOS Databases (2010−2022)

Chen,

Zhang

2023

IJSSH

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Embroidery and weaving techniques are part of the cultural heritage and are the fruit of human civilisation. With the improvement of the technical level of the embroidery machine manufacturing industry, the global embroidery Market in 2022 has reached 7.35 billion US dollars, growing by 10.18% year-on-year, making it an economic research field. In this paper, we used WOS databases to search core papers and CiteSpace, a knowledge graph analysis tool, to determine the current status and trends of research in embroidery from 2010 to 2022. Based on the screened articles, the number of publications, research authors and institutions, keyword co-occurrences, and changes in highlighted words were analyzed in this study. The results showed that China, the United States, and the United Kingdom are the leading researchers in embroidery. Chinese scholars have had an interdisciplinary trend recently and have begun to publish abroad actively. The results of these studies have provided an opportunity for scholars in the field of embroidery to study the cultural connotation and innovative design of embroidery. These results point out the direction for scholars in the field of embroidery research and innovation, identify the shortcomings of each in the current situation of research in China and overseas, find a sustainable path for the development of embroidery craft, and promote the exchange and mutual appreciation of civilizations.

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RETRACTED: Color perception and recognition method for Guangdong embroidery image based on discrete mathematical model

Cited by 5 publications

References 13 publications

Image Color Recognition and Optimization Based on Deep Learning

Image Color Recognition and Optimization Based on Deep Learning

CPRM: Color perception and representation model for fabric image based on color sensitivity of human visual system

Hot Spots and Frontiers in Embroidery Research: A Visualization Analysis via CiteSpace Based on WOS Databases (2010−2022)

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